Malaysian Journal of Computer Science最新文献

{"title":"PREDICTION OF CONGESTIONS USING BASIC TRAFFIC UNIT","authors":"Khairani Abd. Majid, S. Ramli, Sharifah Aishah Syed Ali","doi":"10.22452/mjcs.sp2021no1.2","DOIUrl":"https://doi.org/10.22452/mjcs.sp2021no1.2","url":null,"abstract":"In any form of traffic, whether it is physical or digital, the main problem that sparks a lot of interest for researchers is congestion. This paper discusses a study of congestion around toll plazas. A newly formulated model called Basic Traffic Unit (BTU) is introduced from previous research. BTU is a representation of a basic network connected to form a larger network. A simulation study is conducted and some queuing theories are applied to calculate the measure of performance. Two sets of data from different modes of toll payment are collected. The same two types of payments are simulated and the measure of performance is recorded. The two types of payments from the collected real data are used to calculate the measure of performance using the formula developed by the BTU. This study demonstrates that the results from simulated data can be used to compare with the results from the real-time data using the formula developed by a static model of BTU to predict possible congestions. Comparing results from both methods validates the claim that BTU is useful for predicting congestions.","PeriodicalId":49894,"journal":{"name":"Malaysian Journal of Computer Science","volume":" ","pages":""},"PeriodicalIF":0.6,"publicationDate":"2021-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46198833","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A NEW MODEL OF PARALLEL PARTICLE SWARM OPTIMIZATION ALGORITHM FOR SOLVING NUMERICAL PROBLEMS","authors":"Poria Pirozmand, Hamidreza Alrezaamiri, A. Ebrahimnejad, H. Motameni","doi":"10.22452/mjcs.vol34no4.5","DOIUrl":"https://doi.org/10.22452/mjcs.vol34no4.5","url":null,"abstract":"Evolutionary algorithms are suitable methods for solving complex problems. Many changes have thus been made on their original structures in order to obtain more desirable solutions. Parallelization is a suitable technique to decrease the runtime of the algorithm, and therefore, to obtain solutions with higher quality. In this paper, a new algorithm is proposed with two approaches, which is based on a parallelization technique with shared memory architecture. In the proposed algorithm, the search space is firstly decomposed into multiple equal and independent subspaces. Then, a subtask is performed on each subspace simultaneously in a parallel manner which leads to providing more qualified solutions. Splitting the search space into smaller subspaces causes the algorithm to find optimal solutions in each region in an easier way. The algorithm RAPSO is improved with applying a new acceleration coefficient which has been named IRAPSO. In the proposed algorithm, the IRAPSO is used as the subtask. For the sake of testing the proposed algorithm, fourteen well-known benchmarks of numerical optimizing problems are inspected. Then, the proposed algorithm is compared with algorithms PPBO and PSOPSO that were both based on the island model. The results of the proposed algorithm are much better than those of the other two algorithms.","PeriodicalId":49894,"journal":{"name":"Malaysian Journal of Computer Science","volume":" ","pages":""},"PeriodicalIF":0.6,"publicationDate":"2021-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42266818","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"FEATURE SELECTION AND CLASSIFICATION INTEGRATED METHOD FOR IDENTIFYING CITED TEXT SPANS FOR CITANCES ON IMBALANCED DATA","authors":"Jen-Yuan Yeh, Cheng-Jung Tsai, Tien-Yu Hsu, J. Lin, Pei-Cheng Cheng","doi":"10.22452/mjcs.vol34no4.3","DOIUrl":"https://doi.org/10.22452/mjcs.vol34no4.3","url":null,"abstract":"Recent studies in scientific paper summarization have explored a new form of structured summary for a reference paper by grouping all cited and citing sentences together by facet. This involves three main tasks: (1) identifying cited text spans for citances (i.e., citing sentences), (2) classifying their discourse facets, and (3) generating a structured summary from the cited text spans and citances. This paper focuses on the first task, and approaches the task as binary classification to distinguish relevant pairs of citances and reference sentences from irrelevant pairs. We propose a new method that integrates feature selection and classification techniques to enhance classification performance. The proposed method investigates combinations of six feature selection methods (χ2-Statistics, Information Gain, Gain Ratio, Relief-F, Significance Attribute Evaluation, and Symmetrical Uncertainty), and five classification algorithms (k-Nearest Neighbors, Decision Tree, Support Vector Machine, Naïve Bayes, and Random Forest). Additionally, to address imbalanced data during training, we apply SMOTE (Synthetic Minority Over-sampling Technique) to introduce synthetic biases towards the minority. Experiments are conducted using the CL-SciSumm corpora to compare the effect of feature selection applied to classification. The results reveal the benefits of feature selection in significantly boosting performance of F1 score metric, and show that our method is competitive to the state-of-the-art methods in the CL-SciSumm evaluations.","PeriodicalId":49894,"journal":{"name":"Malaysian Journal of Computer Science","volume":"1 1","pages":""},"PeriodicalIF":0.6,"publicationDate":"2021-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41496917","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"REDUCING INTERRUPTS AMONG ROBOTS IN QUANTUM-BEHAVED SWARM EXPLORATION WITH MR-LEACH","authors":"Zati Hakim Azizul Hasan, Duaa Abdel Fattah Mehiar, C. Loo","doi":"10.22452/mjcs.vol34no4.1","DOIUrl":"https://doi.org/10.22452/mjcs.vol34no4.1","url":null,"abstract":"A quantum-behaved robot exploration algorithm such as the Quantum Robotic Darwinian Particle Swarm Optimization (QRDPSO) gives stable swarm movement in unstructured conditions but suffers from communication interruptions. This paper examines the Multi-hop Routing with Low Energy Adaptive Clustering Hierarchy (MR-LEACH) to improve the inter-connectivity in the QRDPSO. The MR-LEACH identifies partitions in the network into multi-hop network paths. The multi-hop network paths allow all robots to exchange information without unnecessarily restricting the swarm’s range explicitly. As a result, the QRDPSO with MR-LEACH shows seamless inter-connectivity among the robots, lowering power consumption and increasing robots’ lifetime. Interestingly, this paper also shows that the QRDPSO can reach a faster optimal solution when adopting other communication protocols such as the Ad-hoc On-Demand Distance Vector (AODV) communication schema. However, swarm endurance and reduced robot loss are considered vital resources over convergence speed for a swarm robot exploration in unstructured scenarios, such as search and rescue missions.","PeriodicalId":49894,"journal":{"name":"Malaysian Journal of Computer Science","volume":" ","pages":""},"PeriodicalIF":0.6,"publicationDate":"2021-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49555386","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"TWO-STEP MODEL FOR EMOTION DETECTION ON TWITTER USERS: A COVID-19 CASE STUDY IN MALAYSIA","authors":"Chempaka Seri Abdul Razak, S. H. Ab. Hamid, Hasni Meon, Hema A/P Subramaniam, N. B. Anuar","doi":"10.22452/mjcs.vol34no4.4","DOIUrl":"https://doi.org/10.22452/mjcs.vol34no4.4","url":null,"abstract":"Human emotion is often a reflection of one’s behaviour that leads to awareness of one’s mental health. Emotion detection on Twitter users specifically gains attention as it generates information that is useful in the field of psychology and linguistics. However, most existing works related to the subject analysed the emotion of a tweet based on the number of keywords or phrases in it, thus resulting in false annotations and eventually false judgement of the user’s emotion. This paper proposes a two-step model with high and reliable accuracy to detect the emotion of Twitter users based on the semantic meaning of the tweets they posted. The first step classified the emotion of each tweet using four different deep learning techniques. The second step detected the emotion of the user based on the proposed statistical post-level features and a boosting technique. Then, Kappa’s agreement score method was implemented to validate both models. The first step achieved 0.9482 in accuracy while the second step achieved 0.9683 in accuracy. To further validate such highly accurate result, a case study was conducted, and a web-based system was developed to analyse the emotion of college students during the COVID-19 pandemic. Additionally, our analysis corresponded to most of the current reports on the pandemic which further proved the reliability of the developed model.","PeriodicalId":49894,"journal":{"name":"Malaysian Journal of Computer Science","volume":"29 1","pages":""},"PeriodicalIF":0.6,"publicationDate":"2021-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"68662700","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"CNN BASED METHOD FOR MULTI-TYPE DISEASED ARECANUT IMAGE CLASSIFICATION","authors":"S. B. Mallikarjuna, P. Shivakumara, Vijeta Khare, Vinay Kumar N, Basavanna M, U. Pal, Poornima B","doi":"10.22452/mjcs.vol34no3.3","DOIUrl":"https://doi.org/10.22452/mjcs.vol34no3.3","url":null,"abstract":"Arecanut image classification is a challenging task to the researchers and in this paper a new combined approach of multi-gradient images and deep convolutional neural networks for multi-type arecanut image classification is presented. To enhance the fine details in arecanut images affected by different diseases, namely, rot, split and rot-split, we propose to explore multiple-Sobel masks for convolving with the input image. Although, the images suffer from distortion due to disease infection, this masking operation helps to enhance the fine details. We believe that the fine details provide vital clues for classification of normal, rot, split and rot-split images. To extract such clues, we explore the combination of multi-gradient and AlexNet by feeding enhanced images as input. Implementation results on the four-class dataset indicate that the approach proposed is superior in terms of classification rate, recall, precision and F-measures. The same conclusion can be drawn from the results of comparative study of proposed method with the existing methods.","PeriodicalId":49894,"journal":{"name":"Malaysian Journal of Computer Science","volume":" ","pages":""},"PeriodicalIF":0.6,"publicationDate":"2021-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42070602","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"AN EXTENSION OF THE OUTLIER MAP FOR VISUALIZING THE CLASSIFICATION RESULTS OF THE MULTI-CLASS SUPPORT VECTOR MACHINE","authors":"M. Mohammadi, M. Sarmad, N. Arghami","doi":"10.22452/mjcs.vol34no3.5","DOIUrl":"https://doi.org/10.22452/mjcs.vol34no3.5","url":null,"abstract":"The main objective of this study is a graphical display of the results of the high (as well as the low) dimensional multi-class support vector machine classification. Additionally, we will visually be able to detect the outliers and misclassified observations by using this graphical tool. The “outlier map” as a successful graphical outlier detection tool of robust statistics is extended in this paper. In fact, this is a bilateral extension concerning the misclassified and outlying observations recognition. The most important feature of this extension is creating two types of discriminative boundaries to segregate the data and detect the outlying observations. For this purpose, we employed the simple but efficient concept of the “confidence interval”, which is computed for the mean of decision function of support vector machine and then, “thresholding” technique. After that, the efficiency of the outlier map in terms of the preciseness of the correct outlier identification has been tested by the classification accuracy. Moreover, we deployed the margin width “before” and “after” outlier detection as the other criterion to assess the preciseness of the correct outlier identification. We conducted an empirical study based on the proposed method on the simulated and several well-known real datasets. It shows the effectiveness of our proposed method by increasing the “margin width” and gaining a higher classification accuracy.","PeriodicalId":49894,"journal":{"name":"Malaysian Journal of Computer Science","volume":" ","pages":""},"PeriodicalIF":0.6,"publicationDate":"2021-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43619794","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"VIDEO POPULARITY PREDICTION USING STACKED BILSTM LAYERS","authors":"Neeti Sangwan, Vishal Bhatnagar","doi":"10.22452/mjcs.vol34no3.2","DOIUrl":"https://doi.org/10.22452/mjcs.vol34no3.2","url":null,"abstract":"Social media is now not only limited to being a life event sharing platform, but it also has evolved as a monetary medium. Advertisements showing on popular videos may result in more sales conversion. So it is of utmost interest to predict the popularity of videos before uploading it on the platform. In this research article, we propose a deep learning algorithm to predict the popularity of YouTube videos. With the content and temporal features of the YouTube videos dataset, we use a novel stack of deep learning layers. We validate the approach with state-of-the-art methods and prove that the proposed complex stacked architecture gives more accurate and stable results. Results are also tested for short duration prediction with a different number of reference days after video publishing.","PeriodicalId":49894,"journal":{"name":"Malaysian Journal of Computer Science","volume":" ","pages":""},"PeriodicalIF":0.6,"publicationDate":"2021-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46953486","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A COMPILATION OF FACTORS ASSOCIATED TO THE GOVERNANCE AND MANAGEMENT OF AGILE PROJECTS: A SYSTEMATIC LITERATURE REVIEW","authors":"Jayasaegaran Sithambaram, Mohd Hairul Nizam Bin Md Nasir, R. Ahmad","doi":"10.22452/mjcs.vol34no3.4","DOIUrl":"https://doi.org/10.22452/mjcs.vol34no3.4","url":null,"abstract":"The demand for project success is increasing, while the number of failed projects are still high. Whilst Project Management Offices help in the governance of Information Technology projects, the trending issues and challenges in Agile projects need a great deal of attention. More organisations are embracing the agile method due to its popularity and the benefits it yields. Literature discusses various issues and challenges, with an absence of a holistic review to determine its frequency, impact, and classification systematically. This study attempts to identify the factors addressed in literature over the last 2 decades, producing a list of factors and ranking them according to the most addressed and the frequency of reference. A systematic literature review was undertaken to identify the relevant literature using specific keywords search and filter, arriving at a final list of 175 selected studies for the analysis work, which was used to identify 37 prominent factors affecting agile project success. The highest number of studies and factors discussed were between years 2014 and 2016. Project Governance faired as the most addressed factor, while People related factors were widely discussed. Current trends are focused on attaining project governance with a sound understanding of the agile principles, by people with the right attitude, knowledge, skills, and the ability to work well with the team. Project governance with the careful implementation of the agile method and its processes in stages, with the right support tools and technology, is most important for project success. Competence of project stakeholders possessing the right attitude, with great collaboration and teamwork capabilities, and the ability to garner a close relationship with the customer and clearly articulate changing requirements is key to delivering successful agile projects. Future work will include the understanding and identification of critical challenges and crucial factors for ensuring agile project management success. It is proposed to expand the research further into the project governance and people-related area.","PeriodicalId":49894,"journal":{"name":"Malaysian Journal of Computer Science","volume":" ","pages":""},"PeriodicalIF":0.6,"publicationDate":"2021-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46060258","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A RIGOROUS APPROACH TO PRIORITIZING CHALLENGES OF WEB-BASED APPLICATION SYSTEMS","authors":"M. Qadir, S. Farid, Mohd Hairul Nizam Bin Md Nasir, A. Akbar","doi":"10.22452/mjcs.vol34no2.1","DOIUrl":"https://doi.org/10.22452/mjcs.vol34no2.1","url":null,"abstract":"Web innovations are unique advancements of software engineering. They are equipped with new apparatuses, novel systems, and revolutionary plans, ready to be used by web application developers and their users. According to their importance for web application improvement, there is a need to locate a fitting approach to adapt to these challenges. Therefore, the core objective of this study is to rank the challenges that were encountered by the developers and users of web-based applications. This study contributes to knowledge by proposing a hierarchical framework for identifying and categorizing the challenges appropriately. An exhaustive list of sixty-nine challenges was formulated, based on extensive literature review. Quantitative in nature, this study uses the survey questionnaire to collect data from 87 experts in the web innovation domain. Various statistical models like the Cronbach’s Alpha, Principal Component Analysis, Stepwise, and Logistics Regression were employed to analyze the data. The stepwise regression was deployed to formulate the hierarchy of the extracted challenges. The outcome of the proposed framework would lead to a more efficient development and utilization of web applications. The limitations and future directions of this study were also discussed.","PeriodicalId":49894,"journal":{"name":"Malaysian Journal of Computer Science","volume":" ","pages":""},"PeriodicalIF":0.6,"publicationDate":"2021-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44665537","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}